Pith. sign in

REVIEW 3 major objections 7 minor 41 references

Quantum diamond microscopy of individual vaterite microspheres containing magnetite nanoparticles

T0 review · 3 major / 7 minor · reviewed 2026-08-16 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read Widefield quantum diamond microscopy measures stray magnetic fields from individual vaterite microspheres and reports a superparamagnetic-to-ferrimagnetic transition between 10-nm and 20-nm embedded magnetite nanoparticles.

desk verdict Solid single-particle QDM imaging of MNP-loaded vaterite, but the phase-transition headline is undercut by an unmeasured loading confound and a 10x error in the magnetization values used to compute particle counts. read the letter →

arxiv 2504.17312 v1 pith:6KXK3X24 submitted 2025-04-24 physics.bio-ph physics.app-ph

Mona Jani , Hani Barhum , Janis Alnis , Mohammad Attrash , Tamara Amro , Nir Bar-Gill , Toms Salgals , Pavel Ginzburg
show 1 more author
Ilja Fescenko
This is my paper · ORCID
classification physics.bio-phphysics.app-ph
keywords NVcentersvateritemagneticimagingquantumsensorsnanoparticlesmagnetiteFe3O4ODMR
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

Using nitrogen-vacancy centers in diamond as a field sensor, the authors map the stray magnetic field of individual porous vaterite microspheres loaded with magnetite nanoparticles of three sizes. Beads carrying 5-nm or 10-nm particles show peak-to-peak stray fields of about $41\ \mu$T, while beads carrying 20-nm particles show about $12\ \mu$T. The paper interprets this step-like drop as a transition from superparamagnetic to ferrimagnetic behavior between 10 and 20 nm, expressed as a marked reduction in total magnetization. Fits to finite-element simulations also yield the magnetized volume of each bead and indicate that each microsphere holds thousands of nanoparticles. The value for a sympathetic reader is a fast, widefield route to screen magnetic carriers for targeted drug delivery and MRI contrast.

What carries the argument

The carrying mechanism is the NV-diamond sensor: a roughly 200-nm-thick layer of nitrogen-vacancy centers near the diamond surface, interrogated by optically detected magnetic resonance (ODMR). The frequency splitting of the NV spin resonances gives the component of the stray field along the NV axis through the Zeeman relation $f_+ - f_- = 2\gamma B$ (with $f_+ + f_-$ used above 102.5 mT), and a 400×400 pixel camera records this shift over a 26×26 µm area. Fitting measured profiles to finite-element models of uniformly magnetized spheres yields a "magnetization diameter" and volume magnetization, and the count of captured nanoparticles follows from $N = V_{\text{ms}}M_{\text{ms}}/(V_{\text{np}}M_{\text{np}})$.

What would settle it

Measure the iron content per bead (for example, by single-particle ICP-MS or calibrated EDS) for many beads of each size and compare it with the stray-field amplitude. If 20-nm beads carry proportionally less iron while the magnetite's per-mass magnetization is unchanged, the phase-transition claim would be unsupported; if iron loading is comparable across sizes, the drop in stray field would confirm it.

Watch

Extended reading notes

Core claim

The central claim is that widefield quantum diamond microscopy can quantitatively map the magnetization of individual MNP-loaded vaterite microspheres several micrometers in size. Under a 222 mT external field, measured dipole-like stray-field patterns match finite-element simulations of uniformly magnetized spheres, and the peak-to-peak amplitudes cluster at $41 \pm 1\ \mu$T for 5-nm and 10-nm superparamagnetic Fe3O4 beads versus $12 \pm 1\ \mu$T for 20-nm ferrimagnetic Fe3O4 beads. The authors conclude that a phase transition from superparamagnetic to ferrimagnetic (called ferromagnetic in the Conclusion) behavior occurs between 10 and 20 nm, seen as a drop in total magnetization, and they estimate thousands of MNPs per bead, for example about 4,400 20-nm particles in an 8-µm bead. They also note explicitly that the magnetic pattern is insensitive to the radial distribution of particles within the bead, so surface-loaded and volume-loaded beads with the same total moment look alike.

Load-bearing premise

The phase-transition conclusion assumes that the lower stray-field amplitude for 20-nm-loaded beads reflects lower intrinsic magnetization rather than fewer nanoparticles loaded per bead; the paper itself notes that larger particles may fail to enter the vaterite pores and provides no independent iron-loading measurement to break this degeneracy.

Editorial extensions

If this is right

  • Beads with 5-nm and 10-nm magnetite produce roughly three times the stray-field amplitude of 20-nm beads, so nanoparticle size can be used to tune the magnetic contrast of carriers.
  • Each bead concentrates thousands of nanoparticles, with estimates of about 4,400 20-nm particles in an 8-µm bead and 3,800 10-nm particles in a 3-µm magnetized volume, supporting the loading capacity of vaterite.
  • Because the width of the magnetic profile tracks the magnetized volume, the method can flag beads with non-uniform magnetization, as in Microsphere B which appears 9.4 µm optically but 3 µm magnetically.
  • At roughly 0.1 mM concentration, the authors estimate T2 relaxation times could be shortened by 20–50%, enough to produce MRI contrast.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the interpretation holds, the stray-field amplitude could serve as a non-destructive, batch-level gauge for the effective magnetic moment of carrier beads, bypassing dissolution and bulk magnetometry.
  • A direct extension would test the phase-transition claim by pairing QDM with per-bead iron quantification (for example, single-particle ICP-MS or calibrated EDS); the paper itself leaves this explanation degenerate with a loading-permeability alternative.
  • Sweeping the applied field magnitude and angle could extend the same widefield platform to measure remanence, coercivity, or anisotropy of individual beads, quantities that connect to hyperthermia efficiency.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 7 minor

Summary. The paper applies widefield quantum diamond microscopy (QDM) to map stray magnetic fields of individual vaterite microspheres (3–10 µm) loaded with Fe3O4 nanoparticles of three sizes (5, 10, and 20 nm). The authors measure peak-to-peak stray-field amplitudes under an applied field of 222 mT, reporting 41 ± 1 µT for 5- and 10-nm MNPs and 12 ± 1 µT for 20-nm MNPs. They fit the measured magnetic profiles with finite-element simulations of uniformly magnetized spheres, extracting a 'magnetization diameter' and volume magnetization for each microsphere, from which they estimate the number of captured MNPs (a few thousand per microsphere). The paper interprets the lower stray-field amplitude of 20-nm-MNP-loaded microspheres as evidence of a superparamagnetic-to-ferrimagnetic phase transition between 10-nm and 20-nm MNPs, and discusses implications for MRI contrast agents and drug delivery.

Significance. If the central interpretation is correct, the work demonstrates a useful single-particle magnetic characterization technique for porous biocompatible carriers, with potential relevance to targeted drug delivery and magnetic imaging. The study has clear strengths: it uses a quantitative quantum-sensing method, reports error bars, analyzes more than 35 individual microspheres, and explicitly discusses an alternative explanation (size-dependent pore penetration) for the observed signal drop. However, the phase-transition claim depends on an unverified assumption that the number of MNPs per microsphere is comparable across samples; no independent iron-loading measurement is provided. The paper also contains an order-of-magnitude inconsistency in the magnetization value of 20-nm MNPs between the Methods and Section 3, which affects the derived particle counts. These issues are load-bearing for the main conclusion but could be addressed with additional measurements or a more cautious interpretation.

major comments (3)
  1. [Section 3, Fig. 4 and Conclusion] The central claim of a superparamagnetic-to-ferrimagnetic phase transition between 10-nm and 20-nm MNPs is not supported as stated, because the measured peak-to-peak stray-field amplitude is not normalized by the number or iron mass of MNPs per microsphere. The authors themselves acknowledge in Section 3 that the lower signal for 20-nm MNPs 'may be attributed to the larger diameter of the 20-nm Fe3O4 MNPs, which could limit their ability to penetrate the vaterite pores.' The step-like change in PP amplitude and the similar microsphere size distributions do not rule out a size-dependent loading step, which would produce the same observation. Without an independent iron-loading measurement (e.g., ICP-MS or quantitative EDS on many particles), the data are equally consistent with the same magnetic material at lower concentration, and the phase-transition conclusion is a degenerate interpretation rather than a demonstrated result.
  2. [Methods (Section 2) vs Section 3] The magnetization of the 20-nm Fe3O4 MNPs is stated as 3.8–4.7×10^5 A/m in the Methods paragraph, but Section 3 uses 3.89–4.14×10^6 A/m for the same particles when computing N = (Vms·Mms)/(Vnp·Mnp). This order-of-magnitude inconsistency changes the estimated number of captured MNPs by roughly a factor of 10 and must be corrected. As written, the derived particle counts (e.g., 4412 ± 391 for Microsphere A) are not reliable.
  3. [Section 3, Microsphere A/B comparison] The argument that the 20-nm sample's lower signal reflects an intrinsic magnetic transition is undercut by the authors' own comparison: Microsphere A (20-nm MNPs) contains 4,400 MNPs in a magnetization volume about 19 times larger than Microsphere B (10-nm MNPs) containing 3,800 MNPs. This comparison actually shows a much lower nanoparticle density in the 20-nm-loaded microsphere, supporting the pore-penetration hypothesis rather than a phase transition. The subsequent claim that a 'step-like change' in stray-field amplitude more strongly supports a phase transition than a gradual decrease in NP penetration is not logically justified and should be reworked or supported with direct loading measurements.
minor comments (7)
  1. [Abstract and Conclusion] The text uses 'ferrimagnetic' in the abstract and Section 3, but 'ferromagnetic' in the Conclusion; please use consistent terminology.
  2. [Throughout] The term 'phase transition' is used loosely; the size-dependent superparamagnetic-to-ferrimagnetic crossover in nanoparticles is a blocking phenomenon, not a thermodynamic phase transition. Consider rephrasing to 'size-dependent magnetic behavior change'.
  3. [Section 3, N calculation] The equation for N is presented inline; please number it and define all symbols (Vnp, Mnp, Vms, Mms) at first use to improve readability.
  4. [Section 3, MRI discussion] The T2 contrast-agent discussion is speculative and unsupported by direct relaxation measurements; label it explicitly as an outlook or remove it from the results section.
  5. [Figure 4(b)] The mean stray-field plot would be more informative with individual data points or error bars on the means; currently only the mean values are shown, which hides the scatter visible in Figure 4(a).
  6. [Methods paragraph] The brand name 'Merk' should be 'Merck'.
  7. [Figure 1(b) caption] The TEM density estimate (50–90 MNPs per 200 nm^2) is for 10-nm MNPs only; the text should explicitly note that no equivalent estimate is available for the 20-nm particles.

Circularity Check

2 steps flagged · score 5.0 of 10

Phase-transition claim leans on MNP counts that are refits of the same magnetic profiles they are meant to explain.

  1. fitted input called prediction [Section 3, N calculation (N = (Vms·Mms)/(Vnp·Mnp))]
    "By fitting the measured magnetic profile we can estimate the number (N) of MNPs captured by the vaterite microsphere and contributing to the magnetic signal. Using the volume Vnp of the Fe3O4 MNPs and their magnetization Mnp from specifications, along with the volume Vms and magnetization Mms of the microspheres derived from the fit, we calculate the number of captured MNPs as N = (Vms · Mms)/(Vnp · Mnp)."

    N is not an independent observable: it is algebraically forced by the fitted magnetization Mms (derived from the magnetic profile) and by the externally assumed Mnp and Vnp. The paper later uses these N values as evidence about loading, but N is a rearrangement of the same fitted quantity that reproduces the measured signal, so it cannot independently confirm or refute a loading hypothesis.

  2. fitted input called prediction [Section 3, 'Last hypothesis' paragraph and Section 4 Conclusion]
    "The last hypothesis is supported by the observation that Microsphere B, as shown in Figure 3, contains over 3,800 nanoparticles with a diameter of 10 nm within a 3-µm 'magnetization diameter,' whereas Microsphere A contains more than 4,400 nanoparticles with a diameter of 20 nm, despite having a volume approximately 19 times larger."

    This comparison is offered to rule out the pore-penetration/loading confound, but the quoted nanoparticle counts are derived from the same fitted magnetic profiles that produce the PP amplitudes. The phase-transition conclusion ('This step-like change in stray field amplitude more strongly supports a phase transition ... than a gradual decrease in NP penetration') therefore rests on a quantity that is a refit of the very data it is meant to explain, rather than on an independent iron-loading measurement.

full rationale

The raw widefield QDM measurement of PP stray-field amplitudes is self-contained and not circular: the amplitudes are directly read from magnetic images, and the finite-element fits are used only to extract a magnetization diameter and Mms. The circularity enters when the paper converts the fitted Mms into a particle count N = (Vms·Mms)/(Vnp·Mnp) and then cites those N values as evidence that the 20-nm sample is not simply less loaded. Because N is algebraically forced by the same fitted Mms that reproduces the measured profile, using N to dismiss the pore-penetration confound is model inversion rather than independent confirmation. The conclusion of a superparamagnetic-to-ferrimagnetic phase transition relies on that dismissal, so partial circularity is present. No self-citation chain or imported uniqueness theorem is load-bearing here. Separately, the paper contains a numerical inconsistency: Methods lists Mnp(20 nm) = 3.8–4.7×10^5 A/m, but Section 3 uses 3.89–4.14×10^6 A/m for the same particles, and no independent iron quantification per microsphere is provided, leaving the phase-transition claim vulnerable to the loading confound even apart from the circular N rebuttal.

Assumptions & free parameters 2 free parameters · 4 assumptions · 0 invented entities

The central claims rest on two per-microsphere fit parameters (magnetization diameter and volume magnetization), plus the assumption that literature MNP magnetization applies to the actual particles. There is no independent measure of iron loading per microsphere, which is the key missing constraint for the phase-transition conclusion.

free parameters (2)
  • magnetization diameter (D_mag) = per microsphere, e.g., 8 µm (Microsphere A), 3 µm (Microsphere B)
    Fitted from the width of the measured magnetic dip by comparison to finite-element simulations of uniformly magnetized spheres. It defines the effective extent of the magnetized region inside each vaterite microsphere and is not independently measured.
  • volume magnetization of microsphere (Mms) = per microsphere, e.g., 285 A/m (Microsphere A), 550 A/m (Microsphere B)
    Fitted from the peak-to-peak amplitude of the same magnetic profile. This is the sole source of the net magnetic moment in the model and is used to compute the number of captured MNPs.
assumptions (4)
  • domain assumption The measured stray-field component along the NV axis is quantitatively related to magnetic field via the ODMR splitting 2γB|| = f+ + f- at 222 mT, with the NV quantization axis aligned to the applied field.
    Section 2 (QDM description). This is a standard calibration for NV-diamond magnetometry, but any misalignment or strain shift would propagate directly into the reported Bstr values.
  • domain assumption Each vaterite microsphere's magnetic field is well approximated by a uniformly magnetized sphere of fitted diameter D_mag and uniform magnetization Mms.
    Section 3 (simulation fitting). The model ignores porosity, MNP clustering, and non-uniform radial distributions. The authors state the pattern is insensitive to radial distribution, but the uniform-volume assumption still underpins the N estimate.
  • domain assumption The magnetization values of the specific Fe3O4 nanoparticles used here equal the literature values in Refs 34 and 35.
    Section 2 (methods) and Section 3 (N calculation). The cited values are internally inconsistent and exceed bulk magnetite saturation by up to an order of magnitude, so this assumption is fragile and directly affects the particle count.
  • ad hoc to paper The lower stray-field amplitude for 20-nm-MNP-loaded microspheres is caused by lower intrinsic magnetization (phase transition) and not by lower loading of nanoparticles.
    Section 3, 'Finally, we applied the analysis...'. The authors introduce this assumption to interpret the step-like change as a magnetic phase transition; it is the load-bearing interpretation of the main result.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Quantum diamond microscopy of individual vaterite microspheres containing magnetite nanoparticles." pith.science (2026). https://pith.science/paper/6KXK3X24

@misc{pith2026250417312,
  author       = {Pith},
  title        = {Pith review of: Quantum diamond microscopy of individual vaterite microspheres containing magnetite nanoparticles},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/6KXK3X24}},
  note         = {Machine review of arXiv:2504.17312}
}
read the original abstract

Biocompatible vaterite microspheres, renowned for their porous structure, are promising carriers for magnetic nanoparticles (MNPs) in biomedical applications such as targeted drug delivery and diagnostic imaging. Precise control over the magnetic moment of individual microspheres is crucial for these applications. This study employs widefield quantum diamond microscopy to map the stray magnetic fields of individual vaterite microspheres (3-10 um) loaded with Fe3O4 MNPs of varying sizes (5 nm, 10 nm, and 20 nm). By analyzing over 35 microspheres under a 222 mT external magnetizing field, we measured peak-to-peak stray field amplitudes of 41 uT for 5 nm and 10 nm superparamagnetic MNPs, reflecting their comparable magnetic response, and 12 uT for 20 nm ferrimagnetic MNPs, due to distinct magnetization behavior. Finite-element simulations confirm variations in MNP distribution and magnetization uniformity within the vaterite matrix, with each microsphere encapsulating thousands of MNPs to generate its magnetization. This high-resolution magnetic imaging approach yields critical insights into MNP-loaded vaterite, enabling optimized synthesis and magnetically controlled systems for precision therapies and diagnostics.

Figures

Figures reproduced from arXiv: 2504.17312 by the authors.

Figure 1
Figure 1. Characterization of vaterite microspheres loaded with Fe3O4 magnetic nanoparticles. (a) Schematic illustration of a porous vaterite microsphere (dark gray) loaded with Fe3O4 MNPs (black dots) dispersed within its struc￾ture from the surrounding suspension (gray). (b) High-resolution TEM image of the edge of a vaterite microsphere, reveal￾ing the presence of 10 nm Fe3O4 MNPs. (c) Energy-dispersive X-ray spectroscopy … view at source ↗
Figure 2
Figure 2. Quantum diamond microscope (QDM) for magnetic imaging using NV centers. (a) Energy level diagram of the NV center in diamond, showing optical excitation (green arrow), spin-dependent fluorescence (red), and non-radiative decay via singlet states (gray). (b) Optically detected magnetic resonance (ODMR) spectrum, where fluo￾rescence readout reveals resonance dips at frequencies f+ and f− split by the magnetic field. (… view at source ↗
Figure 3
Figure 3. Optical and magnetic imaging of vaterite microspheres with quantum diamond microscopy. (a) Optical (left) and magnetic (middle) images of a vaterite microsphere uniformly functionalized with 20-nm Fe3O4 magnetic nanoparticles. The corresponding magnetic field profile (right) along the red dashed line reveals a symmetric dipole-like signal with a PP amplitude of 110.9 ± 0.6 µT. (b) Optical and magnetic images of a va… view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: Stray magnetic fields of vaterite microspheres with embedded Fe3O4 MNPs. (a) Stray field measured below vaterite microspheres as a function of their diameter, for different Fe3O4 NP sizes (5-nm, 10-nm, and 20-nm). PP amplitude of the stray magnetic field. (b) Mean stra…

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

41 extracted references · 40 canonical work pages

  1. [1]

    A. S. Vikulina, N. A. Feoktistova, N. G. Balabushevich, A. G. Skirtach, D. Volodkin, Physical Chemistry Chemical Physics 2018, 20, 13 8822

    work page 2018

  2. [2]

    P. A. Demina, M. S. Saveleva, R. A. Verkhovskii, R. A. Anisimov, P. S. Pidenko, Y. I. Svenskaya, BioNanoScience 2024, 15, 1

    work page 2024

  3. [3]

    Huang, A

    Y. Huang, A. G. Skirtach, B. V. Parakhonskiy, Ceramics International 2024, 50, 5 7469

    work page 2024

  4. [4]

    A. M. Ferreira, A. Vikulina, G. W. Cave, M. Loughlin, V. Puddu, D. Volodkin, Journal of Colloid and Interface Science 2023, 631 165. 9

    work page 2023

  5. [5]

    Bahrom, A

    H. Bahrom, A. A. Goncharenko, L. I. Fatkhutdinova, O. O. Peltek, A. R. Muslimov, O. Y. Koval, I. E. Eliseev, A. Manchev, D. Gorin, I. I. Shishkin, R. E. Noskov, A. S. Timin, P. Ginzburg, M. V. Zyuzin, ACS Sustainable Chemistry & Engineering 2019, 7, 23 19142

    work page 2019

  6. [6]

    Harpaz, H

    D. Harpaz, H. Barhom, B. Veltman, P. Ginzburg, E. Eltzov, Colloids and Surfaces B: Biointerfaces 2023, 222 113104

    work page 2023

  7. [7]

    B. V. Parakhonskiy, A. M. Yashchenok, S. Donatan, D. V. Volodkin, F. Tessarolo, R. Antolini, H. M¨ ohwald, A. G. Skirtach,ChemPhysChem 2014, 15, 13 2817

    work page 2014

  8. [8]

    M. H. Azarian, W. Sutapun, Nanocomposites 2024, 11, 1 1

    work page 2024

Show all 41 references
  1. [9]

    Barhum, O

    H. Barhum, O. Peltek, D. S. Kolchanov, M. Amer, T. Amro, H. K. Shamkhi, A. Ushkov, A. A. Goncharenko, M. V. Zyuzin, P. Ginzburg, Chemical Engineering Journal 2024, 497 154714

    2024

  2. [10]

    Barhum, C

    H. Barhum, C. McDonnell, O. Peltek, R. Jain, M. Amer, D. Kain, G. Elad-Sfadia, M. Athamna, P. Blinder, P. Ginzburg, Nano Letters 2024, 24, 27 8232–8239

    2024

  3. [11]

    H. Xia, M. Zhou, X. Wei, X. Zhang, Z. Wu, ACS Omega 2020, 5, 23 14123

    2020

  4. [12]

    Gilad, A

    H. Gilad, A. Ushkov, D. Kolchanov, A. Machnev, T. Salgals, V. Bobrovs, H. Barhum, P. Ginzburg, Laser & Photonics Reviews 2025

    2025

  5. [13]

    Choukrani, B

    G. Choukrani, B. Maharjan, C. H. Park, C. S. Kim, A. R. Kurup Sasikala, Materials Science and Engineering: C 2020, 106 110226

    2020

  6. [14]

    N. E. Markina, A. V. Markin, A. M. Zakharevich, I. Y. Goryacheva, Microchimica Acta 2017, 184, 10 3937

    2017

  7. [15]

    B. V. Parakhonskiy, A. Abalymov, A. Ivanova, D. Khalenkow, A. G. Skirtach, Journal of Applied Physics 2019, 126, 20

    2019

  8. [16]

    B. A. Richards, N. Ristoff, J. Smits, A. J. Perez, I. Fescenko, M. D. Aiello, F. Hubert, Y. Silani, N. Mosavian, M. S. Ziabari, A. Berzins, J. T. Damron, P. Kehayias, D. Egbebunmi, J. E. Shield, D. L. Huber, A. M. Mounce, M. P. Lilly, T. Karaulanov, A. Jarmola, A. Laraoui, V. ...

    2025

  9. [17]

    B. A. Frandsen, C. Read, J. Stevens, C. Walker, M. Christiansen, R. G. Harrison, K. Chesnel, Phys- ical Review Materials 2021, 5, 5

    2021

  10. [18]

    Hajalilou, M

    A. Hajalilou, M. Tavakoli, E. Parvini, The Principle of SQUID Magnetometry and Its Contribution in MNPs Evaluation , 135–155, 2023

    2023

  11. [19]

    C. E. Johnson, J. A. Johnson, H. Y. Hah, M. Cole, S. Gray, V. Kolesnichenko, P. Kucheryavy, G. Goloverda, Hyperfine Interactions 2016, 237, 1

    2016

  12. [20]

    N. L. Adolphi, D. L. Huber, H. C. Bryant, T. C. Monson, D. L. Fegan, J. Lim, J. E. Trujillo, T. E. Tessier, D. M. Lovato, K. S. Butler, P. P. Provencio, H. J. Hathaway, S. A. Majetich, R. S. Larson, E. R. Flynn, Physics in Medicine and Biology 2010, 55, 19 5985

    2010

  13. [21]

    J. F. Araujo, Tahir, S. Arsalani, F. L. Freire, G. Mariotto, M. Cremona, L. A. Mendoza, C. Luz- Lima, Q. Zaman, T. Del Rosso, O. Baffa, A. C. Bruno, Journal of Magnetism and Magnetic Ma- terials 2020, 499 166300

    2020

  14. [22]

    Sebastian, K

    T. Sebastian, K. Schultheiss, B. Obry, B. Hillebrands, H. Schultheiss, Frontiers in Physics 2015, 3

    2015

  15. [23]

    K. J. Kirk, J. N. Chapman, C. D. W. Wilkinson, Journal of Applied Physics 1999, 85, 8 5237

    1999

  16. [24]

    Sievers, K

    S. Sievers, K. Braun, D. Eberbeck, S. Gustafsson, E. Olsson, H. W. Schumacher, U. Siegner, Small 2012, 8, 17 2675–2679. 10

    2012

  17. [25]

    E. V. Levine, M. J. Turner, P. Kehayias, C. A. Hart, N. Langellier, R. Trubko, D. R. Glenn, R. R. Fu, R. L. Walsworth, Nanophotonics 2019, 8, 11 1945

    2019

  18. [26]

    Fescenko, A

    I. Fescenko, A. Laraoui, J. Smits, N. Mosavian, P. Kehayias, J. Seto, L. Bougas, A. Jarmola, V. M. Acosta, Physical Review Applied 2019, 3, 11 034029

    2019

  19. [27]

    Berzins, J

    A. Berzins, J. Smits, A. Petruhins, R. Rimsa, G. Mozolevskis, M. Zubkins, I. Fescenko, Optics Ex- press 2023, 31, 11 17950

    2023

  20. [28]

    M. Jani, R. Lazda, F. Gahbauer, A. Asare, M. Mr´ ozek, A. M. Wojciechowski, W. Gawlik, M. Auzi¸ nˇ s,Journal of Physics D: Applied Physics 2025, 58, 12 125301

    2025

  21. [29]

    Le Sage, K

    D. Le Sage, K. Arai, D. R. Glenn, S. J. DeVience, L. M. Pham, L. Rahn-Lee, M. D. Lukin, A. Ya- coby, A. Komeili, R. L. Walsworth, Nature 2013, 496, 7446 486

    2013

  22. [30]

    Lamichhane, R

    S. Lamichhane, R. Timalsina, C. Schultz, I. Fescenko, K. Ambal, S.-H. Liou, R. Y. Lai, A. Laraoui, Nano Letters 2024, 24, 3 873–880

    2024

  23. [31]

    Lamichhane, E

    S. Lamichhane, E. C. Guevara, I. Fescenko, S.-H. Liou, R. Y. Lai, A. Laraoui, Applied Physics Let- ters 2024, 125, 11 114002

    2024

  24. [32]

    Lamichhane, K

    S. Lamichhane, K. A. McElveen, A. Erickson, I. Fescenko, S. Sun, R. Timalsina, Y. Guo, S.-H. Liou, R. Y. Lai, A. Laraoui, ACS Nano 2023, 17, 9 8694

    2023

  25. [33]

    Mart´ ınez-Mera, M

    I. Mart´ ınez-Mera, M. Espinosa-Pesqueira, R. P´ erez-Hern´ andez, J. Arenas-Alatorre,Materials Let- ters 2007, 61, 23–24 4447

    2007

  26. [34]

    Hadadian, H

    Y. Hadadian, H. Masoomi, A. Dinari, C. Ryu, S. Hwang, S. Kim, B. k. Cho, J. Y. Lee, J. Yoon, ACS Omega 2022, 7, 18 15996

    2022

  27. [35]

    Nkurikiyimfura, Y

    I. Nkurikiyimfura, Y. Wang, B. Safari, E. Nshingabigwi, Journal of Alloys and Compounds 2020, 846 156344

    2020

  28. [36]

    G. B. Sukhorukov, D. V. Volodkin, A. M. G¨ unther, A. I. Petrov, D. B. Shenoy, H. M¨ ohwald,J. Mater. Chem. 2004, 14, 14 2073

    2004

  29. [37]

    Fescenko, Ultra-fast detection of the center frequency of a spectral line from amplitude-weighted average, 2023, URL https://arxiv.org/abs/2303.12544

    I. Fescenko, Ultra-fast detection of the center frequency of a spectral line from amplitude-weighted average, 2023, URL https://arxiv.org/abs/2303.12544

    2023 arXiv

  30. [38]

    Berzins, H

    A. Berzins, H. Grube, R. Lazda, M. A. Hannig, J. Smits, I. Fescenko, Ultramicroscopy 2022, 242 113624

    2022

  31. [39]

    Auzinsh, A

    M. Auzinsh, A. Berzins, D. Budker, L. Busaite, R. Ferber, F. Gahbauer, R. Lazda, A. Wickenbrock, H. Zheng, Physical Review B 2019, 100, 7

    2019

  32. [40]

    Dolgovskiy, I

    V. Dolgovskiy, I. Fescenko, N. Sekiguchi, S. Colombo, V. Lebedev, J. Zhang, A. Weis, Applied Physics Letters 2016, 109 023505

    2016

  33. [41]

    R. E. Noskov, A. Machnev, I. I. Shishkin, M. V. Novoselova, A. V. Gayer, A. A. Ezhov, E. A. Shir- shin, S. V. German, I. D. Rukhlenko, S. Fleming, B. N. Khlebtsov, D. A. Gorin, P. Ginzburg, Ad- vanced Materials 2021, 33, 25. 11

    2021

Pith tools

Reviewed August 16, 2026 · model on record in the stance chip above.